hpaSubset() subsets data by gene name, tissue, cell type, cancer and/or
cell line. The input is the list object generated by hpaDownload() or
as the output of another hpaSubset(). Use hpaListParam() to see
the list of available parameters for a specific list object. Will not work on
isoform data.
hpaListParam() list available variables in downloaded data that can be
used as parameters to subset the data via hpaSubset(). This function
work with the data object generated by hpaDownload() or a previous
call of hpaSubset().
hpaSubset(
data = NULL,
targetGene = NULL,
targetTissue = NULL,
targetCellType = NULL,
targetCancer = NULL,
targetCellLine = NULL
)
hpaListParam(data = NULL)Input the list object generated by hpaDownload() or
hpaSubset()
Vector of strings of HGNC gene symbols. It will be used to subset every dataset in the list object. You can also mix HGNC gene symbols and ensemnbl ids (start with ENSG) and they will be converted to HGNC gene symbols.
Vector of strings of normal tissues. Will be used to
subset the normal_tissue and rna_tissue dataset.
Vector of strings of normal cell types. Will be used to
subset the normal_tissue dataset.
Vector of strings of cancer types. Will be used to subset
the pathology dataset.
Vector of strings of cell lines. Will be used to subset
the rna_cell_line dataset.
hpaSubset will return a list of tibbles as the result of
subsetting, depending on the input data.
The output of hpaListParam() is a list of vectors containing
all subset parameter for the downloaded data.
Other downloadable datasets functions:
hpaDownload(),
hpaExport()
downloadedData <- hpaDownload(downloadList='histology', version='example')
#> Only the followings are example/built-in datasets:
#> - Normal tissue
#> - Pathology
#> - Subcellular location
#> Other datasets will not be loaded
geneList <- c('TP53', 'EGFR')
tissueList <- c('breast', 'cerebellum', 'skin 1')
cancerList <- c('breast cancer', 'glioma', 'melanoma')
subsetData <- hpaSubset(data=downloadedData,
targetGene=geneList,
targetTissue=tissueList,
targetCancer=cancerList)
downloadedData <- hpaDownload(downloadList='histology', version='example')
#> Only the followings are example/built-in datasets:
#> - Normal tissue
#> - Pathology
#> - Subcellular location
#> Other datasets will not be loaded
params <- hpaListParam(data=downloadedData)
params$normal_tissue
#> $tissue
#> [1] "adipose tissue" "adrenal gland" "appendix"
#> [4] "bone marrow" "breast" "bronchus"
#> [7] "caudate" "cerebellum" "cerebral cortex"
#> [10] "cervix" "colon" "duodenum"
#> [13] "endometrium 1" "endometrium 2" "epididymis"
#> [16] "esophagus" "fallopian tube" "gallbladder"
#> [19] "heart muscle" "hippocampus" "kidney"
#> [22] "liver" "lung" "lymph node"
#> [25] "nasopharynx" "oral mucosa" "ovary"
#> [28] "pancreas" "parathyroid gland" "placenta"
#> [31] "prostate" "rectum" "salivary gland"
#> [34] "seminal vesicle" "skeletal muscle" "skin 1"
#> [37] "skin 2" "small intestine" "smooth muscle"
#> [40] "soft tissue 1" "soft tissue 2" "spleen"
#> [43] "stomach 1" "stomach 2" "testis"
#> [46] "thyroid gland" "tonsil" "urinary bladder"
#> [49] "vagina" "N/A" "hypothalamus"
#> [52] "hair" "retina" "lactating breast"
#> [55] "skin" "thymus" "cartilage"
#> [58] "eye" "pituitary gland" "dorsal raphe"
#> [61] "choroid plexus" "substantia nigra" "sole of foot"
#>
#> $cell_type
#> [1] "adipocytes"
#> [2] "glandular cells"
#> [3] "lymphoid tissue"
#> [4] "hematopoietic cells"
#> [5] "myoepithelial cells"
#> [6] "respiratory epithelial cells"
#> [7] "glial cells"
#> [8] "neuronal cells"
#> [9] "cells in granular layer"
#> [10] "cells in molecular layer"
#> [11] "Purkinje cells"
#> [12] "endothelial cells"
#> [13] "neuropil"
#> [14] "squamous epithelial cells"
#> [15] "peripheral nerve/ganglion"
#> [16] "cells in endometrial stroma"
#> [17] "cardiomyocytes"
#> [18] "cells in glomeruli"
#> [19] "cells in tubules"
#> [20] "cholangiocytes"
#> [21] "hepatocytes"
#> [22] "alveolar cells"
#> [23] "macrophages"
#> [24] "germinal center cells"
#> [25] "non-germinal center cells"
#> [26] "ovarian stroma cells"
#> [27] "exocrine glandular cells"
#> [28] "pancreatic endocrine cells"
#> [29] "decidual cells"
#> [30] "trophoblastic cells"
#> [31] "myocytes"
#> [32] "fibroblasts"
#> [33] "keratinocytes"
#> [34] "Langerhans"
#> [35] "melanocytes"
#> [36] "epidermal cells"
#> [37] "smooth muscle cells"
#> [38] "peripheral nerve"
#> [39] "cells in red pulp"
#> [40] "cells in white pulp"
#> [41] "cells in seminiferous ducts"
#> [42] "Leydig cells"
#> [43] "urothelial cells"
#> [44] "N/A"
#> [45] "follicle cells"
#> [46] "chondrocytes"
#> [47] "elongated or late spermatids"
#> [48] "pachytene spermatocytes"
#> [49] "peritubular cells"
#> [50] "preleptotene spermatocytes"
#> [51] "round or early spermatids"
#> [52] "sertoli cells"
#> [53] "spermatogonia cells"
#> [54] "alveolar cells type I"
#> [55] "alveolar cells type II"
#> [56] "basal cells"
#> [57] "ciliated cells (cell body)"
#> [58] "ciliated cells (cilia axoneme)"
#> [59] "ciliated cells (ciliary rootlets)"
#> [60] "ciliated cells (tip of cilia)"
#> [61] "goblet cells"
#> [62] "cells in basal layer"
#> [63] "cells in corneal layer"
#> [64] "cells in spinous layer"
#> [65] "extracellular matrix"
#> [66] "fibrohistiocytic cells"
#> [67] "hair follicles"
#> [68] "langerhans cells"
#> [69] "lymphocytes"
#> [70] "vascular mural cells"
#> [71] "Bergmann glia - cytoplasm/membrane"
#> [72] "Bergmann glia - nucleus"
#> [73] "GLUC cells - cytoplasm/membrane"
#> [74] "GLUC cells - nucleus"
#> [75] "granular cells - cytoplasm/membrane"
#> [76] "granular cells - nucleus"
#> [77] "molecular layer - neuropil"
#> [78] "molecular layer cells - cytoplasm/membrane"
#> [79] "molecular layer cells - nucleus"
#> [80] "processes in granular layer"
#> [81] "processes in molecular layer"
#> [82] "processes in white matter"
#> [83] "Purkinje cells - cytoplasm/membrane"
#> [84] "Purkinje cells - dendrites"
#> [85] "Purkinje cells - nucleus"
#> [86] "synaptic glomeruli - capsule"
#> [87] "synaptic glomeruli - core"
#> [88] "white matter cells - cytoplasm/membrane"
#> [89] "white matter cells - nucleus"
#> [90] "endocrine cells"
#> [91] "enterocytes"
#> [92] "enterocytes - Microvilli"
#> [93] "mucosal lymphoid cells"
#> [94] "glands of Brunner"
#> [95] "paneth cells"
#> [96] "bowman's capsule"
#> [97] "collecting ducts"
#> [98] "distal tubules"
#> [99] "proximal tubules (cell body)"
#> [100] "proximal tubules (microvilli)"
#> [101] "arrector pili muscle cells"
#> [102] "non-ciliated cells"
#> [103] "cytotrophoblasts"
#> [104] "hofbauer cells"
#> [105] "syncytiotrophoblasts - cell body"
#> [106] "syncytiotrophoblasts - microvilli"
#> [107] "sebaceous glands"
#> [108] "eccrine glands"
#> [109] "neuronal projections"
#> [110] "synapses"
#> [111] "cells in cortex/medulla"
#> [112] "cells in cuticle"
#> [113] "cells in external root sheath"
#> [114] "cells in internal root sheath"
#> [115] "enterocytes - Gradient"
#> [116] "ganglion cells"
#> [117] "inner nuclear layer"
#> [118] "inner plexiform layer"
#> [119] "limiting membrane"
#> [120] "nerve fiber layer"
#> [121] "outer plexiform layer"
#> [122] "photoreceptor cells"
#> [123] "pigment epithelial cells"
#> [124] "lactating glandular cells"
#> [125] "cells in zona fasciculata"
#> [126] "cells in zona glomerulosa"
#> [127] "cells in zona reticularis"
#> [128] "medullary cells"
#> [129] "sebaceous cells"
#> [130] "secretory cells"
#> [131] "sweat ducts"
#> [132] "cortical cells"
#> [133] "cells in dentate nucleus"
#> [134] "corneal epithelial cells"
#> [135] "hyaloid membrane"
#> [136] "lens epithelial cells"
#> [137] "lens fiber cells"
#> [138] "cells in anterior"
#> [139] "cells in posterior"
#> [140] "ductal cells"
#> [141] "ependymal cells"
#>